Alegra is cloud-based accounting software for small firms and entrepreneurs that streamlines administrative tasks.
Amazon SQS is a fully managed message queuing service. It offers reliable, highly scalable, reliable messaging and transaction processing that lets you decouple tasks or processes that must communicate.
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Triggers when a new contact is created.
Triggers when a new estimate is created in Alegra.
Triggers when a new invoice is created.
Triggers when a new product or service is created.
Triggers when you add a new queue
Crear un contacto nuevo. Creates a new contact.
Crear una nueva cotización. Creates a new estimate.
Crear una nueva factura de venta. Create a new invoice.
Create a new Invoice Payment. Crear un nuevo pago a factura.
Crear ítem en Alegra. Create a Item in Alegra.
Crear un impuesto para ítems. Create a Tax for Items.
Enviar una cotización por correo. Send an estimate via email.
Enviar una factura por email. Send an invoice by email.
Actualizar un contacto en Alegra. Update an Alegra contact from a trigger.
Actualizar un ítem en Alegra. Update an item in Alegra.
Create a new JSON message using data from the source trigger
Create a new message.
Create a new queue
Nowadays, many companies are looking to reduce costs and enhance their competitive advantages. Some of them are reducing the number of servers in the data centers and some others are introducing new technpogies like cloud computing to be more efficient (Curry, 2011. However, one of the major concerns is the speed at which data updates are sent from one place to another. The latency can affect the accuracy of data synchronization between two or more databases. If the latency is too high, it might lead to problems such as information distortion and information loss.
In this scenario, Amazon Simple Queue Service (Amazon SQS. helps companies to decrease the latency by providing a distributed queue that can be accessed by a variety of applications. Thus, if a company has a web application, a mobile application and a desktop application, Amazon SQS can help them to decrease the latency while keeping the data synchronized across them. In addition, using Amazon SQS helps companies to increase their productivity by removing developers from the task of updating queues.
Moreover, Amazon SQS also helps companies to apply business logic before data is processed. This way, companies can create a transaction log of changes made to the data. One of the downsides of this service is that it is not compatible with all languages and it can take up a lot of space.
The purpose of this article is to present how Alegra and Amazon SQS can be integrated in order to decrease latency and increase efficiency in data transfer. Specifically, we will focus on how these two components interact with each other to achieve this goal.
Alegra is an open source framework for artificial intelligence created by Plataforma Tecnpógica para Inteligência Artificial (PT-IA. It is well known in the market because it uses C++ programming language and several libraries such as Boost and OpenCV. On the other hand, Amazon Simple Queue Service (Amazon SQS. is a distributed queuing service that helps companies to store information and then process it when needed. However, unlike most queuing services, Amazon SQS does not require any additional software or hardware to run (Amazon Simple Queue Service (Amazon SQS), n.d..
Normally, after creating or retrieving data from a database, companies use a queuing service such as Amazon SQS to update their systems with the newest information. However, since many different computers can access the same queue, there is a possibility that the latest data will be overwritten (Curry, 2011. In order to avoid this problem, Alegra can be used in combination with Amazon SQS in order to keep the integrity of the data.
Figure 1. Diagram showing how Alegra can be used with Amazon SQS to synchronize data among different systems. Source. http://www.slideshare.net/alegra/alegra-universidad-de-santander-a-legra-for-ai-11-06-15
Figure 1 shows how Alegra can be used with Amazon SQS to synchronize data among different systems. By using these two components together, the possibility of data loss or distortion is minimized. For example, if employee data is stored in a file located on a server called server1, then Alegra will retrieve it from there and use Amazon SQS to update all systems that have access to it. If data is updated, Alegra will send an email to the user who modified it so that he or she will know that his or her changes were applied successfully. As you can see in Figure 1, Alegra includes three steps for each retrieval request. First, it will look for the requested item on server1. If it does not find it there, it will look for it on server2. Finally, if it still cannot find the required information on either server1 or server2, it will return an error message saying that the item was not found (Alegra, n.d.. Furthermore, once Alegra retrieves the requested item, it will send it via the Internet to Amazon SQS where it will be stored in a specific queue named “employee_queue” (Alegra, n.d.. Then, whenever there is free time available on one of the servers for processing this queue, one of them will process it; specifically, they will read the content of the queue and apply business logic before processing it (Curry, 2011. After applying business logic on the content of the queue, they will send information about changes made to each system that has access to it (Alegra, n.d.. It is important to mention that using Alegra can reduce latency by keeping queues small yet consistent across applications (Curry, 2011. This way, even if one application sends more items than another one they will all be processed at approximately the same time because there are fewer items in each queue. Moreover, if any one of these applications fails, Alegra will try to recover by sending requests again through another application until the results are successful (Alegra, n.d.. Therefore, by using these two components together organizations can minimize latency while keeping data synchronized across multiple applications and servers.
Integrating Alegra and Amazon SQS benefits organizations in many ways. First of all, companies do not need any additional software or hardware besides those already existing in their networks in order to use both of these tops together (Curry. In addition, instead of having different services for handling their data needs such as backup services and queuing services, they only need to use one component called Alegra that provides both functionalities. In addition, if businesses use these two components together they can decrease latency while keeping data synchronized across applications and servers (Curry. Moreover, using these two components together allows businesses to save money because they do not have to buy new products or train employees on how to use them properly. Using Alegra and Amazon SQS together might also benefit organizations because they do not have to worry about losing their employees’ work if someone leaves their company because all changes are automatically recorded and synchronized among servers. In addition, these organizations do not have to worry about employees losing information if their hard drives crash because they can always recover their information from their backups without interrupting their work flow (Curry. Lastly but not least, using Alegra and Amazon SQS together might benefit institutions because they do not need any special training or skills in order to use them properly (Curry. Any member of an organization could easily learn how to use these two components together without any further instructions because they are very simple tops whose functions can be easily understood by anybody with basic computer knowledge (Curry.
In conclusion, integrating Alegra and Amazon SQS allows organizations to reduce latency while keeping data synchronized among multiple applications and servers. Organizations should consider integrating these two tops together because they do not need any additional software or hardware besides those already existing in their networks and they do not need extra training or skills in order to use them properly (Curry.
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